Embodiments according to the invention relate to image/video encoding or decoding and, particularly, to an image encoder and an image decoder as well as a method for providing encoded image data and a method for decoding image data.
The human eye can accommodate luminance in a single view over a range of about 100,000:1 and is capable of distinguishing about 10,000 colors at a given brightness. By comparison, typical computer monitors have a luminance range less than 100:1 and cover about half of the visible color gamut. Despite this difference, most digital image formats are geared to the capabilities of conventional displays, rather than the characteristics of human vision.
Recently, there has been an increased interest in high dynamic range (HDR) images, both captured and synthetic, which permit extended processing and higher fidelity display methods.
HDR images store scene referred images (e.g. “Krawczyk, G., Myszkowski, K., and Seidel, H.-P. 2005 “Perceptual effects in real-time tone mapping.” In SCCG '05: Proc. Of the 21st Spring Conference on Computer Graphics, 195.202.”) rather than display referred images. Such images can cover a dynamic range from faint starlight (10−6 cd/m2) to bright sunlight (108 cd/m2). Eyes can simultaneously perceive dynamic range of five orders of magnitude which is 100,000:1. In order to accommodate such a high dynamic range, most commonly used HDR image formats like e.g. openEXR store images in a triplet of floating point numbers per pixel.
A LogLuv transform (e.g. “Larson, G. W., “Overcoming Gamut and Dynamic Range Limitations in Digital Images,” Proceedings of the Sixth Color Imaging Conference, November 1998.”, “N. Adami, M. Okuda, “Effective color space representation for wavelet based compression of HDR images,” International Conference on Image Analysis and Processing, Modena (2007)”, “D. Springer, A. Kaup,” Lossy Compression of Floating Point High Dynamic Range Images JPEG2000, “International Conference on Image Analysis and Processing, Modena (2007)”) method transforms floating point pixels into integer pixels. Such a scheme starts with transforming floating point RGB values into device independent XYZ color space. Then, XYZ color space is transformed into integer LogLuv color space. For Luminance channel a log based transformation is used. For color channels CIEuv representation is used.